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pro vyhledávání: '"Türkpençe, Deniz"'
Significant progress in the construction of physical hardware for quantum computers has necessitated the development of new algorithms or protocols for the application of real-world problems on quantum computers. One of these problems is the power fl
Externí odkaz:
http://arxiv.org/abs/2307.12678
Autor:
Korkmaz, Ufuk, Türkpençe, Deniz
Today, the competition to build a quantum computer continues, and the number of qubits in hardware is increasing rapidly. However, the quantum noise that comes with this process reduces the performance of algorithmic applications, so alternative ways
Externí odkaz:
http://arxiv.org/abs/2307.12298
Autor:
Korkmaz, Ufuk, Türkpençe, Deniz
The expectation that quantum computation might bring performance advantages in machine learning algorithms motivates the work on the quantum versions of artificial neural networks. In this study, we analyze the learning dynamics of a quantum classifi
Externí odkaz:
http://arxiv.org/abs/2307.12293
Autor:
Korkmaz, Ufuk, Türkpençe, Deniz
The promising performance increase offered by quantum computing has led to the idea of applying it to neural networks. Studies in this regard can be divided into two main categories: simulating quantum neural networks with the standard quantum circui
Externí odkaz:
http://arxiv.org/abs/2307.09017
Autor:
Korkmaz, Ufuk, Türkpençe, Deniz
We investigate the open dynamics of a probe qubit weakly interacting with distinct qubit environments bearing quantum information. We show that the proposed dissipative model yields a binary classification of the reservoir qubits' quantum information
Externí odkaz:
http://arxiv.org/abs/2211.16423
A data classifier is the basic structural unit of an artificial neural network. These classifiers, known as perceptron, make an output prediction over the linear summation of the input information. Quantum versions of artificial neural networks are c
Externí odkaz:
http://arxiv.org/abs/1905.00293
We report that under some specific conditions a single qubit model weakly interacting with information environments can be referred to as a quantum classifier. We exploit the additivity and the divisibility properties of the completely positive (CP)
Externí odkaz:
http://arxiv.org/abs/1810.02261
In this study, we propose a spin-star model for spin-(1/2) particles in order to examine the coherence dynamics of a quantum neural network (QNN) unit. Since quantum computing paradigm promises advantages over their classical counterparts, quantum ve
Externí odkaz:
http://arxiv.org/abs/1806.07251
This study concerns with the dynamics of a quantum neural network unit in order to examine the suitability of simple neural computing tasks. More specifically, we examine the dynamics of an interacting spin model chosen as a candidate of a quantum pe
Externí odkaz:
http://arxiv.org/abs/1709.03276
Publikováno v:
Journal of the Optical Society of America B Vol. 36, Issue 5, pp. 1252-1259 (2019)
We study how the thermalization time of a single radiation cavity-field mode changes drastically depending on the type of the atomic reservoir it interacts. Temporal evolution of the field is analyzed within the micromaser scheme, where each atomic r
Externí odkaz:
http://arxiv.org/abs/1708.03721